A growing number of studies have reported that problematic social networking use (PSNU) is strongly associated with anxiety symptoms. However, due to the presence of multiple anxiety subtypes, existing research findings on the extent of this association vary widely, leading to a lack of consensus. The current meta-analysis aimed to summarize studies exploring the relationship between PSNU levels and anxiety symptoms, including generalized anxiety, social anxiety, attachment anxiety, and fear of missing out. 209 studies with a total of 172 articles were included in the meta-analysis, involving 252,337 participants from 28 countries. The results showed a moderately positive association between PSNU and generalized anxiety (GA), social anxiety (SA), attachment anxiety (AA), and fear of missing out (FoMO) respectively (GA:r = 0.388, 95%CI[0.362, 0.413]; SA:r = 0.437, 95%CI[0.395, 0.478]; AA:r = 0.345, 95%CI[0.286, 0.402]; FoMO:r = 0.496, 95%CI[0.461, 0.529]), and there were different regulatory factors between PSNU and different anxiety subtypes. This study provides the first comprehensive estimate of the association of PSNU with multiple anxiety subtypes, which vary by time of measurement, region, gender, and measurement tool.

The current study endeavored to systematically integrate and quantitatively evaluate the effectiveness of interpersonal psychological interventions for postpartum depression patients. Four electronic databases Pubmed, Embase, Cochrane and Web of Science were employed for literature retrieval, and the search time was from the inception of the database to May 30, 2022. Literature screening and data extraction were performed independently by two researchers. A total of 528 studies were screened, and 9 of them were finally included. There were 1012 subjects, 518 of them were assigned in experimental group and 494 in control. Evidence from interpersonal psychological interventions indicated that the data on postpartum depression, satisfaction with family, and social support in both groups after intervention included: depression score [MD = -2.80, 95%CI (-3.86 to -1.74), P < 0.05], satisfaction score [MD = 8.41, 95%CI (1.49 to -15.33), P < 0.05], and social support score [MD = 1.83, 95%CI (-2.10 to -5.76)] of postpartum depression patients. P values < 0.05 indicated substantial improvement as compared to control. During the research process, it is impossible for the experimental group and the researchers to use double-blind trials simultaneously, which may present a Hawthorne effect, but this can be avoided by general psychological intervention for the control. Interpersonal psychotherapy could improve depression in patients with postpartum depression, but the appropriate intervention time was between 4 and 8 weeks, and it also improved satisfaction with family of patients, and the longer the intervention, the higher the satisfaction with the family.

This study aimed to investigate prefrontal function in patients with generalized anxiety disorder (GAD), major depressive disorder (MDD), and the comorbidity of MDD and GAD (CMG), using the fNIRS-VFT task. And to assess the reliability of functional near-infrared spectroscopy (fNIRS) devices as a clinical aid for diagnostic tools when performing cognitive tasks by building a deep neural network. Including 75 patients with GAD, 75 patients with MDD, 71 patients with CMG, and 75 healthy controls (HC). In the verbal fluency test, hemodynamic responses in the prefrontal cortex were monitored with fNIRS, and differences in oxyhemoglobin levels between the four groups were compared using the Kruskal-Wallis rank sum test. A deep learning model combining the Full Connectivity Layer and the Dropout Layer was trained on the training set (60 %), and data from different brain regions were classified for the type of illness on the test set (40 %). The Receiver Operating Characteristic (ROC) graph was generated for each area of interest. Activation in the prefrontal cortex was significantly lower in all patient groups than healthy controls. Activation in the prefrontal cortex was significantly lower in MDD patients compared with GAD patients and in the left ventrolateral prefrontal cortex in the CMG group compared with GAD patients. There was no significant difference in activation in the prefrontal cortex between MDD and CMG groups. In the right orbitofrontal cortex, the four-classification had the highest accuracy with 60.47 %, and the three-classification had the highest accuracy with 77.19 %. The GAD group had the most significant area under the ROC curve in the left ventrolateral prefrontal cortex (AUC = 0.78). The MDD group had the most significant area under the ROC curve in the left frontopolar prefrontal cortex (AUC = 0.86). The CMG group had the most significant area under the ROC curve in the right orbitofrontal cortex (AUC = 0.73). Activation differences in the prefrontal cortex help to identify GAD patients from MDD patients. Differences in activation in the left ventrolateral prefrontal cortex help to discriminate GAD patients from patients with CMG. fNIRS-VFT task can be used clinically as an adjunctive diagnostic tool for mental disorders.

Major Depressive Disorder (MDD) has a high suicide risk, and current diagnosis of suicidal ideation (SI) mainly relies on subjective tools.Neuroimaging techniques, including functional near-infrared spectroscopy (fNIRS), offer potential for identifying objective biomarkers. fNIRS, with its advantages of non-invasiveness, portability, and tolerance of mild movement, provides a feasible approach for clinical research. However, previous fNIRS studies on MDD and suicidal ideation have inconsistent results due to patient and methodological differences.Traditional machine learning in fNIRS data analysis has limitations, while deep - learning methods like one-dimensional convolutional neural network (CNN) are under-explored. This study aims to use fNIRS to explore prefrontal function in first-episode drug-naive MDD patients with suicidal ideation and evaluate fNIRS as a diagnostic tool via deep learning. A total of 91 first-episode drug-naive MDD patients were included and categorized into two groups based on their scores on the suicidal item of the 17-item Hamilton Depression Rating Scale (HAMD-17): 40 patients with suicidal ideation (SIs) and 51 patients without suicidal ideation (NSIs). Concurrently, 39 healthy controls (HCs) were recruited. We utilized fNIRS to measure the hemodynamic responses in the prefrontal cortex of each group during the verbal fluency task (VFT). A Kruskal-Wallis test was conducted to analyze the changes in oxyhemoglobin concentration among the three groups, and receiver operating characteristic (ROC) curves were generated for each region of interest. Compared to HCs, NSIs exhibited significantly reduced activation in the left dorsolateral prefrontal cortex (lDLPFC), frontopolar prefrontal cortex (FPC), orbitofrontal cortex (OFC), and ventrolateral prefrontal cortex (VLPFC), while SIs showed significantly decreased activation in the entire prefrontal cortex. The activation values of SIs in DLPFC, FPC, and OFC were significantly lower than those of NSIs. The highest accuracy for the three-class classification was observed in the lFPC, reaching 69.80%. The SIs group had the largest area under the ROC curve (AUC = 0.88) in the rFPC, while the NSIs group had the largest area under the ROC curve (AUC = 0.88) in the rDLPFC. The HCs group exhibited the largest area under the ROC curve (AUC = 0.92) in the rDLPFC and rVLPFC. DLPFC, FPC, and OFC may serve as biomarker brain regions for identifying suicidal ideation in first-episode drug-naive MDD patients. The fNIRS-VFT task can be utilized clinically as an auxiliary diagnostic tool for mental disorders.

Background: Growing evidence suggests a relationship between deficits in cognitive control and anxiety. However, studies examining cognitive control within affective contexts (affective control) are limited, and the specific characteristics of affective control in patients with Generalized Anxiety Disorder (GAD) remain unclear. This study investigated whether differences exist in cognitive control under affective contexts.Methods: We conduct our research in a population of GAD patients (n = 50) and a healthy control group (n = 50). The affective flanker task measured affective inhibition, while the affective flexibility task assessed affective shifting capabilities.Results: GAD patients exhibited abnormal affective inhibition, characterized by reduced proactive control related to target stimulus processing and enhanced reactive control associated with distractor resolution. Additionally, GAD patients demonstrated deficits in affective shifting, as indicated by significantly higher shifting costs in both non-affective and affective tasks compared to the healthy control group.Conclusions: The findings reveal that GAD patients display poorer emotion recognition abilities, indicating deficits in affective control compared to healthy individuals. Our study underscores the importance of measuring affective control by delineating it into distinct components.